Water Quality Monitoring and Management: Basis, Technology and Case Studies presents recent innovations in operations management for water quality monitoring. It highlights the cost of using and choosing smart sensors with advanced engineering approaches that have been applied in water quality monitoring management, including area coverage planning and sequential scheduling. In parallel, the book covers newly introduced technologies like bulk data handling techniques, IoT of agriculture, and compliance with environmental considerations. Presented from a system engineering perspective, the book includes aspects on advanced optimization, system and platform, Wireless Sensor Network, selection of river water quality, groundwater quality detection, and more.
It will be an ideal resource for students, researchers and those working daily in agriculture who must maintain acceptable water quality.
Please Note: This is an On Demand product, delivery may take up to 11 working days after payment has been received.
Table of Contents
1. Sensors in Water Quality Monitoring2. Wireless Sensor Networks in Water Quality Monitoring
3. System and Platform for Water Quality Monitoring
4. Water Quality Evaluation
5. Prediction of Water Quality
6. Water Quality Early Warnings
7. Detection of River Water Quality
8. Water Quality Detection for Lakes
9. Seawater Quality Detection
10. Drinking Water Detection
11. Groundwater Quality Detection
12. Water Quality Monitoring in Aquaculture
13. Detection of Industrial Water Quality
Authors
Daoliang Li College of Information and Electrical Engineering, China Agricultural University, China.College of Information and Electrical Engineering, China Agricultural University, China.
The author is well-recognized internationally, holding executive positions in the key international associations promoting agricultural engineering. He has long experience in teaching related courses including:
Master level and Ph.D. level courses in intelligent information system of agriculture, Systems Engineering, Agricultural advanced sensing, intelligent information processing, Internet of things of agriculture, System analysis and design, Information technologies and Undergraduate courses in Information technology in Agriculture, agriculture expert systems.
Shuangyin Liu College of Information, Guangdong Ocean University, Zhanjiang Guangdong, China.
S. Liu received his B.E. degree in the Department of Computer Science, Air Force Engineering University in 2002 and his M.E. degree in Faculty of Computer, Guangdong University of Technology in 2006. He is a Ph.D. student in the College of Information and Electric Engineering of China Agriculture University. He is a lecturer in the College of Information, Guangdong Ocean University, and he is a member of China Computer Federation. He primary research interests are intelligent information system of agriculture, artificial intelligence, software engineering, computational intelligence.
